On semiparametric regression with O'Sullivan penalized splines

Wand, MP; Ormerod, JT

On semiparametric regression with O'Sullivan penalized splines

Wand, MP

Ormerod, JT

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Publication Type:: Journal Article
Citation:: Australian and New Zealand Journal of Statistics, 2008, 50 (2), pp. 179 - 198
Issue Date:: 2008-06-01

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Field	Value	Language
dc.contributor.author	Wand, MP https://orcid.org/0000-0003-2555-896X	en_US
dc.contributor.author	Ormerod, JT	en_US
dc.date.issued	2008-06-01	en_US
dc.identifier.citation	Australian and New Zealand Journal of Statistics, 2008, 50 (2), pp. 179 - 198	en_US
dc.identifier.issn	1369-1473	en_US
dc.identifier.uri	http://hdl.handle.net/10453/14534
dc.identifier.uri	http://hdl.handle.net/10453/41303
dc.description.abstract	An exposition on the use of O'Sullivan penalized splines in contemporary semiparametric regression, including mixed model and Bayesian formulations, is presented. O'Sullivan penalized splines are similar to P-splines, but have the advantage of being a direct generalization of smoothing splines. Exact expressions for the O'Sullivan penalty matrix are obtained. Comparisons between the two types of splines reveal that O'Sullivan penalized splines more closely mimic the natural boundary behaviour of smoothing splines. Implementation in modern computing environments such as Matlab, r and bugs is discussed. © 2008 Australian Statistical Publishing Association Inc.	en_US
dc.relation.ispartof	Australian and New Zealand Journal of Statistics	en_US
dc.relation.isbasedon	10.1111/j.1467-842X.2008.00507.x	en_US
dc.subject.classification	Statistics & Probability	en_US
dc.title	On semiparametric regression with O'Sullivan penalized splines	en_US
dc.type	Journal Article
utslib.citation.volume	2	en_US
utslib.citation.volume	50	en_US
utslib.for	0104 Statistics	en_US
utslib.for	1403 Econometrics	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Science
pubs.organisational-group	/University of Technology Sydney/Faculty of Science/School of Mathematical and Physical Sciences
utslib.copyright.status	closed_access
pubs.issue	2	en_US
pubs.publication-status	Published	en_US
pubs.volume	50	en_US

Abstract:

An exposition on the use of O'Sullivan penalized splines in contemporary semiparametric regression, including mixed model and Bayesian formulations, is presented. O'Sullivan penalized splines are similar to P-splines, but have the advantage of being a direct generalization of smoothing splines. Exact expressions for the O'Sullivan penalty matrix are obtained. Comparisons between the two types of splines reveal that O'Sullivan penalized splines more closely mimic the natural boundary behaviour of smoothing splines. Implementation in modern computing environments such as Matlab, r and bugs is discussed. © 2008 Australian Statistical Publishing Association Inc.

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http://hdl.handle.net/10453/14534